Rule based model configuration enables configuration logic to itself have dependencies on other elements of configuration, and to make use of the resolved states of those other elements of configuration while performing its own configuration.

In a nutshell, the Software Model is a very declarative way to describe how a piece of software is built and the other components it needs as dependencies in the process. It also provides a new, rule-based engine for configuring a Gradle build. When we started to implement the software model we set ourselves the following goals:

Improve configuration and execution time performance.

Make customizations of builds with complex tool chains easier.

Provide a richer, more standardized way to model different software ecosystems.

Gradle drastically improved configuration performance through other measures. There is no longer any need for a drastic, incompatible change in how Gradle builds are configured. Gradle’s support for building native software and Play Framework applications still use the configuration model.

The term “model space” is used to refer to the formal model, which can be read and modified by rules.

A counterpart to the model space is the “project space”, which should be familiar to readers. The “project space” is a graph of objects (e.g project.repositories, project.tasks etc.) having a Project as its root. A build script is effectively adding and configuring objects of this graph. For the most part, the “project space” is opaque to Gradle. It is an arbitrary graph of objects that Gradle only partially understands.

Each project also has its own model space, which is distinct from the project space. A key characteristic of the “model space” is that Gradle knows much more about it (which is knowledge that can be put to good use). The objects in the model space are “managed”, to a greater extent than objects in the project space. The origin, structure, state, collaborators and relationships of objects in the model space are first class constructs. This is effectively the characteristic that functionally distinguishes the model space from the project space: the objects of the model space are defined in ways that Gradle can understand them intimately, as opposed to an object that is the result of running relatively opaque code. A “rule” is effectively a building block of this definition.

The model space will eventually replace the project space, becoming the only “space”.

The model space is defined by “rules”. A rule is just a function (in the abstract sense) that either produces a model element, or acts upon a model element. Every rule has a single subject and zero or more inputs. Only the subject can be changed by a rule, while the inputs are effectively immutable.

Gradle guarantees that all inputs are fully “realized“ before the rule executes. The process of “realizing” a model element is effectively executing all the rules for which it is the subject, transitioning it to its final state. There is a strong analogy here to Gradle’s task graph and task execution model. Just as tasks depend on each other and Gradle ensures that dependencies are satisfied before executing a task, rules effectively depend on each other (i.e. a rule depends on all rules whose subject is one of the inputs) and Gradle ensures that all dependencies are satisfied before executing the rule.

Model elements are very often defined in terms of other model elements. For example, a compile task’s configuration can be defined in terms of the configuration of the source set that it is compiling. In this scenario, the compile task would be the subject of a rule and the source set an input. Such a rule could configure the task subject based on the source set input without concern for how it was configured, who it was configured by or when the configuration was specified.

One way to define rules is via a RuleSource subclass. If an object extends RuleSource and contains any methods annotated by '@Mutate', then each such method defines a rule. For each such method, the first argument is the subject, and zero or more subsequent arguments may follow and are inputs of the rule.

This rule declares that there is a model element at path "person" (defined by the method name), of type Person. This is the form of the Model type rule for Managed types. Here, the person object is the rule subject. The method could potentially have a body, that mutated the person instance. It could also potentially have more parameters, which would be the rule inputs.

This Mutate rule mutates the person object. The first parameter to the method is the subject. Here, a by-type reference is used as no Path annotation is present on the parameter. It could also potentially have more parameters, that would be the rule inputs.

This Mutate rule effectively adds a task, by mutating the tasks collection. The subject here is the "tasks" node, which is available as a ModelMap of Task. The only input is our person element. As the person is being used as an input here, it will have been realised before executing this rule. That is, the task container effectively depends on the person element. If there are other configuration rules for the person element, potentially specified in a build script or other plugin, they will also be guaranteed to have been executed.

As Person is a Managed type in this example, any attempt to modify the person parameter in this method would result in an exception being thrown. Managed objects enforce immutability at the appropriate point in their lifecycle.

Rule source plugins can be packaged and distributed in the same manner as other types of plugins (see Custom Plugins). They also may be applied in the same manner (to project objects) as Plugin implementations (i.e. via Project.apply(java.util.Map)).

Please see the documentation for RuleSource for more information on constraints on how rule sources must be implemented and for more types of rules.

A model path identifies the location of an element relative to the root of its model space. A common representation is a period-delimited set of names. For example, the model path "tasks" is the path to the element that is the task container. Assuming a task whose name is hello, the path "tasks.hello" is the path to this task.

Currently, any kind of Java object can be part of the model space. However, there is a difference between “managed” and “unmanaged” objects.

A “managed” object is transparent and enforces immutability once realized. Being transparent means that its structure is understood by the rule infrastructure and as such each of its properties are also individual elements in the model space.

An “unmanaged” object is opaque to the model space and does not enforce immutability. Over time, more mechanisms will be available for defining managed model elements culminating in all model elements being managed in some way.

Managed models can be defined by attaching the @Managed annotation to an interface:

By defining a getter/setter pair, you are effectively declaring a managed property. A managed property is a property for which Gradle will enforce semantics such as immutability when a node of the model is not the subject of a rule. Therefore, this example declares properties named firstName and lastName on the managed type Person. These properties will only be writable when the view is mutable, that is to say when the Person is the subject of a Rule (see below the explanation for rules).

Managed properties can be of any scalar type. In addition, properties can also be of any type which is itself managed:

A ManagedSet. A managed set supports the creation of new named model elements, but not their removal.

Only if read/write

ModelSet<Person> getChildren()

A Set or List of scalar types. All classic operations on collections are supported: add, remove, clear…​

Only if read/write

void setUserGroups(List<String> groups)
List<String> getUserGroups()

If the type of a property is itself a managed type, it is possible to declare only a getter, in which case you are declaring a read-only property. A read-only property will be instantiated by Gradle, and cannot be replaced with another object of the same type (for example calling a setter). However, the properties of that property can potentially be changed, if, and only if, the property is the subject of a rule. If it’s not the case, the property is immutable, like any classic read/write managed property, and properties of the property cannot be changed at all.

Managed types can be defined out of interfaces or abstract classes and are usually defined in plugins, which are written either in Java or Groovy. Please see the Managed annotation for more information on creating managed model objects.

As previously mentioned, a rule has a subject and zero or more inputs. The rule’s subject and inputs are declared as “references” and are “bound” to model elements before execution by Gradle. Each rule must effectively forward declare the subject and inputs as references. Precisely how this is done depends on the form of the rule. For example, the rules provided by a RuleSource declare references as method parameters.

A reference is either “by-path” or “by-type”.

A “by-type” reference identifies a particular model element by its type. For example, a reference to the TaskContainer effectively identifies the "tasks" element in the project model space. The model space is not exhaustively searched for candidates for by-type binding; rather, a rule is given a scope (discussed later) that determines the search space for a by-type binding.

A “by-path” reference identifies a particular model element by its path in model space. By-path references are always relative to the rule scope; there is currently no way to path “out” of the scope. All by-path references also have an associated type, but this does not influence what the reference binds to. The element identified by the path must however by type compatible with the reference, or a fatal “binding failure” will occur.

Rules are bound within a “scope”, which determines how references bind. Most rules are bound at the project scope (i.e. the root of the model graph for the project). However, rules can be scoped to a node within the graph. The ModelMap.named(java.lang.String, java.lang.Class) method is an example of a mechanism for applying scoped rules. Rules declared in the build script using the model {} block, or via a RuleSource applied as a plugin use the root of the model space as the scope. This can be considered the default scope.

By-path references are always relative to the rule scope. When the scope is the root, this effectively allows binding to any element in the graph. When it is not, then only the children of the scope can be referenced using "by-path" notation.

When binding by-type references, the following elements are considered:

The scope element itself.

The immediate children of the scope element.

The immediate children of the model space (i.e. project space) root.

For the common case, where the rule is effectively scoped to the root, only the immediate children of the root need to be considered.

Mutating or validating all elements of a given type in some scope is a common use-case. To accommodate this, rules can be applied via the @Each annotation.

In the example below, a @Defaults rule is applied to each FileItem in the model setting a default file size of "1024". Another rule applies a RuleSource to every DirectoryItem that makes sure all file sizes are positive and divisible by "16".

In addition to using a RuleSource, it is also possible to declare a model and rules directly in a build script using the “model DSL”.

💡

The model DSL makes heavy use of various Groovy DSL features. Please have a read of Groovy DSL basics for an introduction to these Groovy features.

The general form of the model DSL is:

model {
«rule-definitions»
}

All rules are nested inside a model block. There may be any number of rule definitions inside each model block, and there may be any number of model blocks in a build script. You can also use a model block in build scripts that are applied using apply from: $uri.

There are currently 2 kinds of rule that you can define using the model DSL: configuration rules, and creation rules.

A configuration rule specifies a path to the subject that should be configured and a closure containing the code to run when the subject is configured. The closure is executed with the subject passed as the closure delegate. Exactly what code you can provide in the closure depends on the type of the subject. This is discussed below.

You should note that the configuration code is not executed immediately but is instead executed only when the subject is required. This is an important behaviour of model rules and allows Gradle to configure only those elements that are required for the build, which helps reduce build time. For example, let’s run a task that uses the "person" object:

A creation rule definition specifies the path of the element to create, plus its public type, represented as a Java interface or class. Only certain types of model elements can be created.

A creation rule may also provide a closure containing the initialization code to run when the element is created. The closure is executed with the element passed as the closure delegate. Exactly what code you can provide in the closure depends on the type of the subject. This is discussed below.

The initialization closure is optional and can be omitted, for example:

You should note that the initialization code is not executed immediately but is instead executed only when the element is required. The initialization code is executed before any configuration rules are run. For example:

Notice that the creation rule appears in the build script after the configuration rule, but its code runs before the code of the configuration rule. Gradle collects up all the rules for a particular subject before running any of them, then runs the rules in the appropriate order.

A ModelMap is basically a map of model elements, indexed by some name. When a ModelMap is used as the subject of a DSL rule, the rule closure can use any of the methods defined on the ModelMap interface.

A rule closure with ModelMap as a subject can also include nested creation or configuration rules. These behave in a similar way to the creation and configuration rules that appear directly under the model block.

As before, a nested creation rule defines a name and public type for the element, and optionally, a closure containing code to use to initialize the element. The code is run only when the element is required in the build.

As before, a nested configuration rule defines the name of the element to configure and a closure containing code to use to configure the element. The code is run only when the element is required in the build.

ModelMap introduces several other kinds of rules. For example, you can define a rule that targets each of the elements in the map. The code in the rule closure is executed once for each element in the map, when that element is required. Let’s run a task that requires all of the children of the "people" element:

Scalar properties in managed types can be assigned CharSequence values (e.g. String, GString, etc.) and they will be converted to the actual property type for you. This works for all scalar types including `File`s, which will be resolved relative to the current project.

The code for this example can be found at samples/modelRules/modelDslCoercion in the ‘-all’ distribution of Gradle.

In the above example, an Item is created and is initialized in setDefaults() by providing the path to the data file. In the item() method the resolved File is parsed to extract and set the data. In the DSL block at the end, the price is adjusted based on the quantity; if there are fewer than 10 remaining the price is doubled, otherwise it is reduced by 50%. The GString expression is a valid value since it resolves to a float value in string form.

Finally, in createDataTask() we add the showData task to display all of the configured values.

The code for this example can be found at samples/modelRules/modelDsl in the ‘-all’ distribution of Gradle.

In the above snippet, the $.person construct is an input reference. The construct returns the value of the model element at the specified path, as its default type (i.e. the type advertised by the Model Report). It may appear anywhere in the rule that an expression may normally appear. It is not limited to the right hand side of variable assignments.

The input element is guaranteed to be fully configured before the rule executes. That is, all of the rules that mutate the element are guaranteed to have been previously executed, leaving the target element in its final, immutable, state.

Most model elements enforce immutability when being used as inputs. Any attempt to mutate such an element will result in a runtime error. However, some legacy type objects do not currently implement such checks. Regardless, it is always invalid to attempt to mutate an input to a rule.

The built-in ModelReport task displays a hierarchical view of the elements in the model space. Each item prefixed with a + on the model report is a model element and the visual nesting of these elements correlates to the model path (e.g. tasks.help). The model report displays the following details about each model element:

Table 3. Model report - model element details

Detail

Description

Type

This is the underlying type of the model element and is typically a fully qualified class name.

Value

Is conditionally displayed on the report when a model element can be represented as a string.

Creator

Every model element has a creator. A creator signifies the origin of the model element (i.e. what created the model element).

Rules

Is a listing of the rules, excluding the creator rule, which are executed for a given model element. The order in which the rules are displayed reflects the order in which they are executed.

The rule engine that was part of the Software Model will be deprecated. Everything under the model block will be ported as extensions to the current model. Native users will no longer have a separate extension model compared to the rest of the Gradle community, and they will be able to make use of the new variant aware dependency management. For more information, see the blog post on the state and future of the software model.